Dataset Information

Association of the triglyceride-glucose index with subclinical left ventricular dysfunction in type 2 diabetes mellitus patients: A retrospective cross-sectional study.

ABSTRACT:

Aims/introduction

The triglyceride-glucose (TyG) index is a simple and reliable indicator of insulin resistance, and is associated with the development and poor outcomes of cardiovascular disease. Subclinical left ventricular dysfunction (SLVD) is frequently detected in approximately one-third of diabetes patients, but it has not been established whether the TyG index correlates with SLVD. We carried out this research to evaluate the relationship between the TyG index and SLVD in type 2 diabetes mellitus patients.

Materials and methods

This was a cross-sectional and observational study of 183 type 2 diabetes mellitus inpatients at Nanjing Drum Tower Hospital, Nanjing, China. The TyG index and homeostasis model assessment 2 estimates for insulin resistance (HOMA2-IR) were calculated from biochemical measurements, and speckle-tracking echocardiography was carried out. According to global longitudinal strain (GLS) by echocardiography, participants were categorized into the SLVD (GLS <18%) group or the non-SLVD (GLS ≥18%) group.

Results

In comparison with non-SLVD participants, SLVD participants had higher insulin resistance, as reflected by elevated TyG and HOMA2-IR indices, as well as a higher body mass index, waist circumference and triglyceride level (P < 0.05 for each). When grouped by TyG index tertiles, an elevated TyG index was correlated with other cardiometabolic risk factors, as well as a decrease in GLS. In the multivariate logistic regression analyses, the TyG index was an independent risk factor for SLVD in type 2 diabetes mellitus patients (odds ratio 2.047, 95% confidence interval 1.07-3.914, P = 0.03), whereas HOMA2-IR was not.

Conclusions

The TyG index is independently associated with SLVD in type 2 diabetes mellitus patients and is a more reliable indicator of SLVD than HOMA2-IR.

SUBMITTER: Sun QC

PROVIDER: S-EPMC10360383 | biostudies-literature | 2023 Aug

REPOSITORIES: biostudies-literature

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Publications

Association of the triglyceride-glucose index with subclinical left ventricular dysfunction in type 2 diabetes mellitus patients: A retrospective cross-sectional study.

Sun Qi-Chao QC Liu Jie J Meng Ran R Zhang Ning N Yao Jing J Yang Fan F Zhu Da-Long DL

Journal of diabetes investigation 20230507 8

<h4>Aims/introduction</h4>The triglyceride-glucose (TyG) index is a simple and reliable indicator of insulin resistance, and is associated with the development and poor outcomes of cardiovascular disease. Subclinical left ventricular dysfunction (SLVD) is frequently detected in approximately one-third of diabetes patients, but it has not been established whether the TyG index correlates with SLVD. We carried out this research to evaluate the relationship between the TyG index and SLVD in type 2 ...[more]

PMID: 37151188

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Project description:BackgroundSubclinical LV dysfunction (LVD) identifies heart failure (HF) risk in type 2 diabetes mellitus (T2DM). We sought the extent to which clinical scores (ARIC-HF, WATCH-DM), natriuretic peptides (NTpBNP) and troponin (hs-TnT) were associated with subclinical LV dysfunction (LVD). These associations could inform the ability of these tests to identify which patients should undergo echocardiography.MethodsParticipants with T2DM were prospectively recruited from three community-based populations. ARIC-HF risk at 4 years and WATCH-DM scores were calculated from clinical data. NTpBNP and hs-TnT were measured using an electro-chemiluminescence assay. All underwent a comprehensive echocardiogram. We calculated the sensitivity and specificity of clinical scores and biomarkers to identify abnormal global longitudinal strain (GLS ≥ -16%)), diastolic function (E/e' ≥ 14 or e' < 8 cm/s), left atrial volume index (LAV > 34 ml/m2) and LV hypertrophy (LV mass index > 88 g/m2 (F) > 102 g/m2(M)).ResultsOf 804 participants (median age 69 years [inter-quartile range (IQR) 65-73], 36% female), clinical scores suggested significant HF risk (median ARIC-HF 8% [IQR 4-12]; WATCH-DM 10 points [IQR 8-12]), and the median NTpBNP was 50 pg/mL [IQR 25-101] and hs-TnT 9.6 pg/mL [IQR 6.8-13.6]. Abnormal GLS was present in 126 (17%), elevated E/e' in 114 (15%), impaired e' in 629 (78%), increased LAV in 351 (44%) and LV hypertrophy in 113 (14%). After adjustments for age, body-mass index, and renal function, each standard deviation increase in NTpBNP was associated with a GLS increase of 0.32 (p < 0.001) and hs-TnT increase by 0.26 (p < 0.001). Similar trends were observed with ARIC-HF (standardised β = 0.22, p < 0.001) and WATCH-DM (standardised β = 0.22, p < 0.001) in univariable analyses. However, none of the risk assessment tools provided satisfactory discrimination for abnormal GLS (AUC 63%), diastolic indices (e' AUC 54-61%) or LV mass (AUC 59-67%). At a sensitivity of 90%, there was an unacceptably low (< 50%) specificity.ConclusionAlthough risk assessment based on clinical scores or biomarkers would be desirable to stratify HF risk in people with T2DM, they show a weak relationship with subclinical LVD.

Project description:BackgroundRecent guidelines propose N-terminal pro-B-type natriuretic peptide (NT-proBNP) for recognition of asymptomatic left ventricular (LV) dysfunction (Stage B Heart Failure, SBHF) in type 2 diabetes mellitus (T2DM). Wavelet Transform based signal-processing transforms electrocardiogram (ECG) waveforms into an energy distribution waveform (ew)ECG, providing frequency and energy features that machine learning can use as additional inputs to improve the identification of SBHF. Accordingly, we sought whether machine learning model based on ewECG features was superior to NT-proBNP, as well as a conventional screening tool-the Atherosclerosis Risk in Communities (ARIC) HF risk score, in SBHF screening among patients with T2DM.MethodsParticipants in two clinical trials of SBHF (defined as diastolic dysfunction [DD], reduced global longitudinal strain [GLS ≤ 18%] or LV hypertrophy [LVH]) in T2DM underwent 12-lead ECG with additional ewECG feature and echocardiography. Supervised machine learning was adopted to identify the optimal combination of ewECG extracted features for SBHF screening in 178 participants in one trial and tested in 97 participants in the other trial. The accuracy of the ewECG model in SBHF screening was compared with NT-proBNP and ARIC HF.ResultsSBHF was identified in 128 (72%) participants in the training dataset (median 72 years, 41% female) and 64 (66%) in the validation dataset (median 70 years, 43% female). Fifteen ewECG features showed an area under the curve (AUC) of 0.81 (95% CI 0.787-0.794) in identifying SBHF, significantly better than both NT-proBNP (AUC 0.56, 95% CI 0.44-0.68, p < 0.001) and ARIC HF (AUC 0.67, 95%CI 0.56-0.79, p = 0.002). ewECG features were also led to robust models screening for DD (AUC 0.74, 95% CI 0.73-0.74), reduced GLS (AUC 0.76, 95% CI 0.73-0.74) and LVH (AUC 0.90, 95% CI 0.88-0.89).ConclusionsMachine learning based modelling using additional ewECG extracted features are superior to NT-proBNP and ARIC HF in SBHF screening among patients with T2DM, providing an alternative HF screening strategy for asymptomatic patients and potentially act as a guidance tool to determine those who required echocardiogram to confirm diagnosis. Trial registration LEAVE-DM, ACTRN 12619001393145 and Vic-ELF, ACTRN 12617000116325.

Project description:IntroductionLeft ventricular global longitudinal strain (GLS) is considered to be the first marker of diabetes mellitus-related subclinical cardiac dysfunction, but whether it is attributable to fat mass and distribution remains uncertain. In this study, we explored whether fat mass, especially fat mass in the android area, is associated with subclinical systolic dysfunction before the onset of cardiac disease.MethodsWe conducted a single-center prospective cross-sectional study between November 2021 and August 2022 on inpatients of the Department of Endocrinology, Nanjing Drum Tower Hospital. We included 150 patients aged 18-70 years with no signs, symptoms, or history of clinical cardiac disease. Patients were evaluated with speckle tracking echocardiography and dual energy X-ray absorptiometry. The cutoff values for subclinical systolic dysfunction were set at a global longitudinal strain (GLS) < 18%.ResultsAfter adjusting for sex and age, patients with GLS < 18% had a higher mean (± standard deviation) fat mass index (8.06 ± 2.39 vs. 7.10 ± 2.09 kg/m2, p = 0.02), higher mean trunk fat mass (14.9 ± 4.9 vs. 12.8 ± 4.3 kg, p = 0.01), and higher android fat mass (2.57 ± 1.02 vs. 2.18 ± 0.86 kg, p = 0.02) than those in the GLS ≥ 18%. Partial correlation analysis showed that the fat mass index, truck fat mass, and android fat mass were negatively correlated with GLS after adjusting for sex and age (all p < 0.05). Adjusted for traditional cardiovascular metabolic factors, fat mass index (odds ratio [OR] 1.27, 95% confidence interval [CI] 1.05-1.55, p = 0.02), trunk fat mass (OR 1.13, 95% CI 1.03-1.24, p = 0.01), and android fat mass (OR 1.77, 95% CI 1.16-2.82, p = 0.01) were independent risk factors for GLS < 18%.ConclusionAmong patients with type 2 diabetes mellitus without established clinical cardiac disease, fat mass, especially android fat mass, was associated with subclinical systolic dysfunction independently of age and sex.

Dataset Information

Association of the triglyceride-glucose index with subclinical left ventricular dysfunction in type 2 diabetes mellitus patients: A retrospective cross-sectional study.

Aims/introduction

Materials and methods

Results

Conclusions

Publications

Association of the triglyceride-glucose index with subclinical left ventricular dysfunction in type 2 diabetes mellitus patients: A retrospective cross-sectional study.

Similar Datasets

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